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Comprehensive analysis of Transcription Factors identified novel prognostic biomarker in human bladder cancer.

ABSTRACT: Background: Transcriptional factors (TFs) are responsible for regulating the transcription of pro-oncogenes and tumor suppressor genes in the process of tumor development. However, the role of these transcription factors in Bladder cancer (BCa) remains unclear. And the main purpose of this research is to explore the possibility of these TFs serving as biomarkers for BCa. Methods: We analyzed the differential expression of TFs in BCa from The Cancer Genome Atlas (TCGA) online database, identified 408 up-regulated TFs and 751down-regulated TFs. We obtained some hub genes via WGCNA model and detected the RNAs level in BCa cells and tissues. Then, the relationship between the expression and clinicopathological parameters was further investigated. Kaplan-Meier curves and the log-rank test were carried out to analyze the relationship between NFATC1, AKNA and five-TFs combination and overall survival (OS). And RT-PCR assay was conducted to further consolidate and verify these results. Results: There were significant differences in the expression of five TFs (CBX7, AKNA, HDAC4, EBF2 and NFATC1) between bladder cancer and normal bladder tissue. In BCa tissue and cell lines, the five TFs were frequently down-regulated, and closely related to poor prognosis. Moreover, the RT-PCR results of five TFs in bladder cancer and normal bladder tissue were consistent with the database results, and reduced TFs could significantly induce or restrain the transcription of many critical factors. The expression level of AKNA and NFATC1 could serve as independent biomarker to predict the overall survival (P<0.05). And the above five TFs combined detection of bladder cancer has higher sensitivity and specificity. Furthermore, differential neutrophils expression between high-risk and low-risk were found, which consolidated the role and function of the five TFs combination model in the progression of BCa. Conclusions: Our analysis effectively provides a newly TFs-associated prognostic model for bladder cancer. The combination of five identified-TFs is an independent prognostic biomarker, which could serve as a more effective therapeutic target for BCa patients.

SUBMITTER: Liao Y

PROVIDER: S-EPMC8364643 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe tumor microenvironment (TME) plays a crucial role in the initiation and progression of cancer. Bladder cancer (BLCA) is a malignant tumor of the genitourinary system. Its heterogeneity results in significant differences in the prognosis of patients. To date, this is still a huge challenge for clinical treatment. In recent years, more and more evidence showed that dysregulation of transcription factors (TFs) plays an important role in tumor progression, invasion, and metastasis. Unfortunately, the role of TFs on the tumor microenvironment in bladder cancer is unclear.MethodsThe original data of BLCA and corresponding adjacent tissues were obtained from The Cancer Genome Atlas (TCGA) database. TFs were downloaded from the Animal Transcription Factor DataBase (Animal TFDB). Intersection analysis was used to obtain TFs that were differentially expressed between tumor and adjacent tissues. Gene Set Cancer Analysis (GSCALite) and CIBERSORT software were used to reveal the key differentially expressed TFs (DE-TFs). Subsequently, UALCAN and Human Protein Atlas (HPA) databases were used to disclose the expression of key DE-TFs in BLCA. The K-M curve divulged the relationship between the key DE-TFs and the patient's overall survival (OS), and the univariate and multivariate Cox regression analyses were conducted to explore independent prognostic factors. The cluster profiler package and Gene Set Enrichment Analysis (GSEA) were used for functional enrichment of genes related to the key DE-TFs. Finally, CIBERSORT software analyzed the immune landscape of BLCA.ResultsWe obtained a total of 117 BLCA-related DE-TFs. Among them, ETV7 was identified as the key DE-TFs due to its association with the autophagy activation pathway and various immune cells in cancer. Online databases of UALCAN and HPA indicated that ETV7 was overexpressed in tumors and negatively correlated with tumor severity. The K-M curve showed that the OS of patients with high expression of ETV7 was poor, which indicated that it was an independent prognostic factor. Functional enrichment of 87 DEGs between ETV7-high and -low expression groups indicated that it was closely related to the immune response and the functions of a variety of immune cells. Finally, CIBERSORT results proved that the high and low expression of ETV7 also caused significant differences in the tumor immune microenvironment of patients.ConclusionOverall, we proved that the transcription factor ETV7 was a novel prognostic factor, which may improve the individualized outcome prediction in BLCA by regulating the tumor immune microenvironment.

Project description:It is becoming increasingly clear that no single marker will have the sensitivity and specificity necessary to be used on its own for diagnosis/prognosis of tumors. Interpatient and intratumor heterogeneity provides overwhelming odds against the existence of such an ideal marker. With this in mind, our laboratory has been applying a long term systematic approach to identify multiple biomarkers that can be used for clinical purposes. As a result of these studies, we have identified and reported several candidate biomarker proteins that are deregulated in bladder cancer. Following the conceptual biomarker development phases proposed by the Early Detection Research Network, we have taken some of the most promising candidate proteins into postdiscovery validation studies, and here we report on the characterization of one such biomarker, the bladder cancer-associated protein (BLCAP), formerly termed Bc10. To characterize BLCAP protein expression and cellular localization patterns in benign bladder urothelium and urothelial carcinomas (UCs), we used two independent sets of samples from different patient cohorts: a reference set consisting of 120 bladder specimens (formalin-fixed as well as frozen biopsies) and a validation set consisting of 2,108 retrospectively collected UCs with long term clinical follow-up. We could categorize the UCs examined into four groups based on levels of expression and subcellular localization of BLCAP protein and showed that loss of BLCAP expression is associated with tumor progression. The results indicated that increased expression of this protein confers an adverse patient outcome, suggesting that categorization of staining patterns for this protein may have prognostic value. Finally, we applied a combinatorial two-marker discriminator using BLCAP and adipocyte-type fatty acid-binding protein, another UC biomarker previously reported by us, and found that the combination of the two markers correlated more closely with grade and/or stage of disease than the individual markers. The implications of these results in biomarker discovery are discussed.

Project description:BackgroundIron-sulfur cluster assembly 1 (ISCA1) has a significant effect on respiratory complexes and energy metabolism. Although there is some evidence that ISCA1 gene expression impacts energy metabolism and consequently has a role in tumorigenesis and cancer metastasis in different types of malignancies, no systematic pan-cancer study of the ISCA1 has been conducted. As a result, we sought to investigate ISCA1's predictive value in 33 cancer types as well as its possible immunological function.MethodsWe included the pan-cancer expression profile dataset and clinical data from the public database. Firstly, the single-sample Gene Set Enrichment Analysis (ssGSEa) approach was employed for analyzing the immune link in pan-cancer, while the limma package was utilized for analyzing the differential expression in cancer species. Subsequently, ciberport, MCP-counter, TIMER2, quanTIseq, and xCELL were employed for analyzing bladder cancer (BLCA)'s immune infiltration. Least absolute shrinkage and selection operator (Lasso) were employed for choosing the best gene to develop the immune risk scoring model.ResultsISCA1 gene expression was positively related to four immune signatures (chemokine, immunostimulator, MHC, and receptor) in BLCA. Samples of BLCA were sorted into two groups by the best cut-off of ISCA1 expression degree. The group with a high level of ISCA1 expression had a higher risk, suggesting that the ISCA1 gene was a risk factor in BLCA, and its high expression resulted in a poorer prognosis. Additionally, it was noted that ISCA1 was positively linked with these immune checkpoints. Moreover, there was a considerable positive link between ISCA1 and different immune properties in subgroups with different immune checkpoint inhibiting responses. Finally, an immune risk scoring model was made and it showed a better score in comparison to that of TIDE.ConclusionISCA1 can be a prognostic marker for a variety of cancers, particularly BLCA. Its high level of expression has a deleterious impact on the prognosis of BLCA patients. This strongly shows that ISCA1 is a significant prognostic factor for BLCA and that it could be used as a new prognostic detection target and treatment approach.

Project description:BackgroundColon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients.MethodsAlteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features.ResultsThe prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient.ConclusionThe novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients.

Project description:Prolyl 4-hydroxylase, beta polypeptide (P4HB) protein is an endoplasmic reticulum (ER) molecular chaperone protein and has been reported to be overexpressed in multiple tumor types. However, the role of P4HB in bladder cancer (BLCA) has not yet been elucidated. The aim of the present study was to investigate the prognostic value of P4HB and the association between clinicopathological characteristics and P4HB in BLCA. P4HB expression levels were assessed through The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blot analysis in BLCA tissues and cells. A total of 69 pairs of tumor and normal samples were used to analyze the expression of P4HB via immunohistochemical staining. A co-expression network and functional enrichment analyses were conducted to investigate the biological function of P4HB in BLCA. The protein-protein interaction (PPI) network was constructed by Search Tool for the Retrieval of Interacting Genes. The results showed that P4HB was highly expressed in BLCA cells and tissues. The area under the curve value for P4HB expression to discriminate between tumor and normal tissues was up to 0.888 (95% CI: 0.801-0.975; P<0.001) and 0.881 (95% CI: 0.825-0.937; P<0.001) in TCGA database and our database, respectively. Furthermore, the expression level of P4HB was an independent risk factor for overall survival (OS) and recurrence-free survival (RFS) by univariate and multivariate analyses. Kaplan-Meier survival analysis demonstrated that high P4HB expression was associated with low OS and RFS. Pathway enrichment analysis suggested that P4HB was involved in protein processing in the endoplasmic reticulum (ER), including N-glycan modification and protein metabolic processes responding to ER stress. PPI analysis revealed that the potential targets of P4HB were mainly involved in posttranslational protein modification and response to ER stress. In conclusion, the expression level of P4HB aid in identifying patients with early-stage BLCA and predicting the prognosis of BLCA. Therefore, P4HB may be a novel diagnostic and prognostic biomarker for BLCA.

Project description:BackgroundE2F transcription factors (E2Fs) are a group of genes encoding a family of transcription factors in higher eukaryotes. They are involved in a variety of cellular functions and are up-regulated in many tissues and organs. However, the expression level, genetic variation, molecular mechanism, and biological function of different E2Fs in PAAD and its relationship with the prognosis and immune infiltration in patients with PAAD have not been fully elucidated.MethodsIn this study, we investigated the mRNA expression level, genetic variation, prognostic value and gene-gene interaction network of E2Fs in PAAD using the Oncomine, GEPIA, Kaplan Meier plotter, cBioPortal, GeneMANIA, STRING and Metascape database. Then, the relationship between E2Fs expression and tumor immune invasion was studied by using the TIMER database. Finally, we confirmed the expression of E2Fs in PAAD by IHC.ResultsThe transcription levels of E2F1/3/5/8 are obviously up-regulated in PAAD and the high expression of E2F2/3/6/8 was apparently associated with the tumor stage of patients with PAAD. The abnormal expression of E2F1/2/3/4/5/7/8 in PAAD patients is related to the clinical outcome of PAAD patients. We also found that PAAD tissues have higher expression levels of E2F1/3/5/8 compared with adjacent normal tissues. The function of E2Fs and its neighboring genes is mainly related to the transcription initiation of the RNA polymerase II promoter. The functions of E2Fs and its neighboring proteins are mainly related to cell cycle, virus carcinogenesis, FoxO signaling pathway, TGF-β signaling pathway, transcriptional disorders in cancer and Wnt signaling pathway. We also found that the expression of E2Fs was significantly correlated with immune infiltrates, including B cells, CD8+ T cells, CD4+T cells, neutrophils, macrophages, and dendritic cells.ConclusionsOur study may provide new insights into the choice of immunotherapy targets and prognostic biomarkers in PAAD patients.

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Comprehensive analysis of Transcription Factors identified novel prognostic biomarker in human bladder cancer.

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